Paper List

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Summary of In-context Learning Can Re-learn Forbidden Tasks, by Sophie Xhonneux et al.
Summary of Model-based Rl For Mean-field Games Is Not Statistically Harder Than Single-agent Rl, by Jiawei Huang et al.
Summary of Implicit Bias and Fast Convergence Rates For Self-attention, by Bhavya Vasudeva et al.
Summary of A Sampling Theory Perspective on Activations For Implicit Neural Representations, by Hemanth Saratchandran et al.
Summary of Mixture Density Networks For Classification with An Application to Product Bundling, by Narendhar Gugulothu et al.
Summary of Gpt-4 Generated Narratives Of Life Events Using a Structured Narrative Prompt: a Validation Study, by Christopher J. Lynch et al.
Summary of Learning Uncertainty-aware Temporally-extended Actions, by Joongkyu Lee et al.
Summary of Scalable Wasserstein Gradient Flow For Generative Modeling Through Unbalanced Optimal Transport, by Jaemoo Choi et al.
Summary of Minecraft-ify: Minecraft Style Image Generation with Text-guided Image Editing For In-game Application, by Bumsoo Kim et al.
Summary of Accurate Lora-finetuning Quantization Of Llms Via Information Retention, by Haotong Qin et al.
Summary of Mitigating Privacy Risk in Membership Inference by Convex-concave Loss, By Zhenlong Liu et al.
Summary of Implicit Diffusion: Efficient Optimization Through Stochastic Sampling, by Pierre Marion et al.
Summary of Linearizing Models For Efficient Yet Robust Private Inference, by Sreetama Sarkar et al.
Summary of Multi-timescale Ensemble Q-learning For Markov Decision Process Policy Optimization, by Talha Bozkus and Urbashi Mitra
Summary of Differentially Private Deep Model-based Reinforcement Learning, by Alexandre Rio et al.
Summary of Asynchronous Diffusion Learning with Agent Subsampling and Local Updates, by Elsa Rizk et al.
Summary of Fedaa: a Reinforcement Learning Perspective on Adaptive Aggregation For Fair and Robust Federated Learning, by Jialuo He et al.
Summary of Flashback: Understanding and Mitigating Forgetting in Federated Learning, by Mohammed Aljahdali et al.
Summary of Offline Actor-critic Reinforcement Learning Scales to Large Models, by Jost Tobias Springenberg et al.
Summary of Succinct Interaction-aware Explanations, by Sascha Xu et al.
Summary of Training-free Message Passing For Learning on Hypergraphs, by Bohan Tang et al.
Summary of Tighter Learning Guarantees on Digital Computers Via Concentration Of Measure on Finite Spaces, by Anastasis Kratsios et al.
Summary of Attnlrp: Attention-aware Layer-wise Relevance Propagation For Transformers, by Reduan Achtibat et al.
Summary of Classification Under Nuisance Parameters and Generalized Label Shift in Likelihood-free Inference, by Luca Masserano et al.
Summary of Investigating Generalization Behaviours Of Generative Flow Networks, by Lazar Atanackovic et al.
Summary of Kix: a Knowledge and Interaction-centric Metacognitive Framework For Task Generalization, by Arun Kumar et al.
Summary of Revisiting Early-learning Regularization When Federated Learning Meets Noisy Labels, by Taehyeon Kim et al.
Summary of Exploring Learning Complexity For Efficient Downstream Dataset Pruning, by Wenyu Jiang et al.
Summary of An Examination on the Effectiveness Of Divide-and-conquer Prompting in Large Language Models, by Yizhou Zhang et al.
Summary of Principled Preferential Bayesian Optimization, by Wenjie Xu et al.
Summary of Noise Contrastive Alignment Of Language Models with Explicit Rewards, by Huayu Chen et al.
Summary of Trade-offs Of Diagonal Fisher Information Matrix Estimators, by Alexander Soen and Ke Sun
Summary of Attention As Robust Representation For Time Series Forecasting, by Peisong Niu et al.
Summary of Task-customized Masked Autoencoder Via Mixture Of Cluster-conditional Experts, by Zhili Liu et al.
Summary of Knowledge Graphs Meet Multi-modal Learning: a Comprehensive Survey, by Zhuo Chen et al.
Summary of Optimizing For Roc Curves on Class-imbalanced Data by Training Over a Family Of Loss Functions, By Kelsey Lieberman et al.
Summary of Taser: Temporal Adaptive Sampling For Fast and Accurate Dynamic Graph Representation Learning, by Gangda Deng et al.
Summary of Everybody Prune Now: Structured Pruning Of Llms with Only Forward Passes, by Lucio Dery et al.
Summary of Version Age-based Client Scheduling Policy For Federated Learning, by Xinyi Hu et al.
Summary of Adaptive Activation Functions For Predictive Modeling with Sparse Experimental Data, by Farhad Pourkamali-anaraki et al.
Summary of Segmentation-free Connectionist Temporal Classification Loss Based Ocr Model For Text Captcha Classification, by Vaibhav Khatavkar et al.
Summary of Difftori: Differentiable Trajectory Optimization For Deep Reinforcement and Imitation Learning, by Weikang Wan et al.
Summary of Neural Circuit Diagrams: Robust Diagrams For the Communication, Implementation, and Analysis Of Deep Learning Architectures, by Vincent Abbott
Summary of Veras: Verify Then Assess Stem Lab Reports, by Berk Atil et al.
Summary of Universal Neural Functionals, by Allan Zhou et al.
Summary of Qgfn: Controllable Greediness with Action Values, by Elaine Lau et al.
Summary of Learning Fair Ranking Policies Via Differentiable Optimization Of Ordered Weighted Averages, by My H. Dinh et al.
Summary of Adabatchgrad: Combining Adaptive Batch Size and Adaptive Step Size, by Petr Ostroukhov et al.
Summary of Feature Learning As Alignment: a Structural Property Of Gradient Descent in Non-linear Neural Networks, by Daniel Beaglehole et al.
Summary of Convergence For Natural Policy Gradient on Infinite-state Queueing Mdps, by Isaac Grosof et al.
Summary of Safety Filters For Black-box Dynamical Systems by Learning Discriminating Hyperplanes, By Will Lavanakul et al.
Summary of Analyzing Adversarial Inputs in Deep Reinforcement Learning, by Davide Corsi et al.
Summary of Exploring Hierarchical Classification Performance For Time Series Data: Dissimilarity Measures and Classifier Comparisons, by Celal Alagoz
Summary of No Dimensional Sampling Coresets For Classification, by Meysam Alishahi and Jeff M. Phillips
Summary of Do Transformer World Models Give Better Policy Gradients?, by Michel Ma et al.
Summary of Graph Convolutional Network As a Fast Statistical Emulator For Numerical Ice Sheet Modeling, by Maryam Rahnemoonfar et al.
Summary of Examining Modality Incongruity in Multimodal Federated Learning For Medical Vision and Language-based Disease Detection, by Pramit Saha et al.
Summary of An Information Theoretic Approach to Quantify the Stability Of Feature Selection and Ranking Algorithms, by Alaiz-rodriguez et al.
Summary of Biked++: a Multimodal Dataset Of 1.4 Million Bicycle Image and Parametric Cad Designs, by Lyle Regenwetter et al.
Summary of Classifying Spam Emails Using Agglomerative Hierarchical Clustering and a Topic-based Approach, by F. Janez-martino et al.
Summary of Interactive Symbolic Regression Through Offline Reinforcement Learning: a Co-design Framework, by Yuan Tian et al.
Summary of Three Pathways to Neurosymbolic Reinforcement Learning with Interpretable Model and Policy Networks, by Peter Graf and Patrick Emami
Summary of Learning on Multimodal Graphs: a Survey, by Ciyuan Peng et al.
Summary of Opening the Ai Black Box: Program Synthesis Via Mechanistic Interpretability, by Eric J. Michaud et al.
Summary of More Agents Is All You Need, by Junyou Li et al.
Summary of Graph Neural Network and Ner-based Text Summarization, by Imaad Zaffar Khan et al.
Summary of Illuminate: a Novel Approach For Depression Detection with Explainable Analysis and Proactive Therapy Using Prompt Engineering, by Aryan Agrawal
Summary of Personalized Language Modeling From Personalized Human Feedback, by Xinyu Li et al.
Summary of Tag-llm: Repurposing General-purpose Llms For Specialized Domains, by Junhong Shen et al.
Summary of Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method For Autonomous Driving, by Wensheng Su et al.
Summary of Online Learning Approach For Survival Analysis, by Camila Fernandez (lpsm) et al.
Summary of Apiq: Finetuning Of 2-bit Quantized Large Language Model, by Baohao Liao et al.
Summary of Flowpg: Action-constrained Policy Gradient with Normalizing Flows, by Janaka Chathuranga Brahmanage et al.
Summary of Designing Deep Neural Networks For Driver Intention Recognition, by Koen Vellenga et al.
Summary of Crashformer: a Multimodal Architecture to Predict the Risk Of Crash, by Amin Karimi Monsefi et al.
Summary of Estimating On-road Transportation Carbon Emissions From Open Data Of Road Network and Origin-destination Flow Data, by Jinwei Zeng and Yu Liu and Jingtao Ding and Jian Yuan and Yong Li
Summary of Enhancement Of Bengali Ocr by Specialized Models and Advanced Techniques For Diverse Document Types, By Akm Shahariar Azad Rabby et al.
Summary of A Resource Model For Neural Scaling Law, by Jinyeop Song et al.
Summary of Towards Understanding Inductive Bias in Transformers: a View From Infinity, by Itay Lavie et al.
Summary of Assessing the Brittleness Of Safety Alignment Via Pruning and Low-rank Modifications, by Boyi Wei et al.
Summary of Learning Mirror Maps in Policy Mirror Descent, by Carlo Alfano et al.
Summary of On Parameter Estimation in Deviated Gaussian Mixture Of Experts, by Huy Nguyen and Khai Nguyen and Nhat Ho
Summary of Bellman Conformal Inference: Calibrating Prediction Intervals For Time Series, by Zitong Yang et al.
Summary of Context in Public Health For Underserved Communities: a Bayesian Approach to Online Restless Bandits, by Biyonka Liang et al.
Summary of Priorboost: An Adaptive Algorithm For Learning From Aggregate Responses, by Adel Javanmard et al.
Summary of Generative Flows on Discrete State-spaces: Enabling Multimodal Flows with Applications to Protein Co-design, by Andrew Campbell et al.
Summary of Asymptotics Of Feature Learning in Two-layer Networks After One Gradient-step, by Hugo Cui et al.
Summary of Beyond Explaining: Xai-based Adaptive Learning with Shap Clustering For Energy Consumption Prediction, by Tobias Clement and Hung Truong Thanh Nguyen and Nils Kemmerzell and Mohamed Abdelaal and Davor Stjelja
Summary of Randomized Confidence Bounds For Stochastic Partial Monitoring, by Maxime Heuillet et al.
Summary of Example-based Explanations For Random Forests Using Machine Unlearning, by Tanmay Surve and Romila Pradhan
Summary of Efficientvit-sam: Accelerated Segment Anything Model Without Accuracy Loss, by Zhuoyang Zhang et al.
Summary of Navigating Complexity: Toward Lossless Graph Condensation Via Expanding Window Matching, by Yuchen Zhang and Tianle Zhang and Kai Wang and Ziyao Guo and Yuxuan Liang and Xavier Bresson and Wei Jin and Yang You
Summary of A Sober Look at Llms For Material Discovery: Are They Actually Good For Bayesian Optimization Over Molecules?, by Agustinus Kristiadi et al.
Summary of Strong Convexity-guided Hyper-parameter Optimization For Flatter Losses, by Rahul Yedida et al.
Summary of Majority Kernels: An Approach to Leverage Big Model Dynamics For Efficient Small Model Training, by Hanna Mazzawi et al.
Summary of Salad-bench: a Hierarchical and Comprehensive Safety Benchmark For Large Language Models, by Lijun Li et al.
Summary of Causal Representation Learning From Multiple Distributions: a General Setting, by Kun Zhang et al.
Summary of Nito: Neural Implicit Fields For Resolution-free Topology Optimization, by Amin Heyrani Nobari et al.
Summary of Pac Learnability Under Explanation-preserving Graph Perturbations, by Xu Zheng et al.
Summary of Improved Off-policy Training Of Diffusion Samplers, by Marcin Sendera et al.